WSN lifetime optimization through controlled sink mobility and packet buffering
WSN lifetime optimization through controlled sink mobility and packet buffering
复制标题
通过受控接收器移动性和数据包缓冲来优化 WSN 生命周期
DOI：
10.1109/giis.2013.6684346
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Y. Challal
中科院分区：
文献类型：
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作者：
Tifenn Rault;A. Bouabdallah;Y. Challal
最大化能量受限的无线传感器网络的生命周期是一个非常具有挑战性的问题。它已被证明，使用一个移动的汇可以显着增加网络的寿命，通过平衡节点之间的负载。然而，在现有的解决方案中，节点或者通过多跳向汇点发送数据，这引起由于中继过程的能量消耗，或者节点存储数据直到汇点到达它们附近，这通常需要无限的缓冲区容量，或者如果缓冲区具有固定大小则引起缓冲区溢出。在本文中，我们提出了一种新的方法，其中节点发送他们的数据通过多跳路径的长度减少提供节点的可能性，以缓冲数据，同时等待汇接近（不一定在节点范围内），这免除了更多的传感器中继这些数据。这种策略可以节省能源，同时确保不会因缓冲区溢出而丢失数据。我们使用线性规划（LP）模型优化有限的缓冲区容量和受控的移动的信宿的无线传感器网络的生命周期的问题。对于任意的拓扑结构，我们的LP确定在每个可能的位置，节点之间的数据传输速率和缓冲的数据包数量的sink逗留时间。与以前的模型相比，我们的解决方案实现了更好的生命周期，并能够生成和传输更多的数据到移动的汇。我们表明，我们的计划也更好地平衡节点之间的负载。最后，我们从数值结果中得出一个分布式的无线传感器网络中的数据收集算法。我们通过模拟表明，我们的方法利用延迟节能，我们比较其性能对单跳和多跳转发协议。
Maximizing the lifetime of energy constrained wireless sensor networks is a very challenging issue. It has been demonstrated that the use of a mobile sink can significantly increase the network lifetime by balancing the load among nodes. However, in existing solutions, nodes either send their data through multihop towards the sink which induces energy consumption due to relaying process, or the nodes store the data until the sink comes at their vicinity, which usually requires an infinite buffer capacity or induces buffer overflow if the buffer is of fixed size. In this paper, we propose a new approach in which nodes send their data through multihop path of reduced length by offering nodes the possibility to buffer data while waiting the sink coming closer (not necessarily at node range), which exempts more sensors from relaying these data. This strategy allows to save energy, while ensuring no data is lost due to buffer overflow. We model the problem of optimizing WSN lifetime with limited buffer capacity and controlled mobile sink using a Linear Program (LP). For arbitrary topologies, our LP determines the sink sojourn times at each possible location, the data transfer rates between nodes and the buffered packets quantities. Compared to previous models, our solution achieves better lifetime and enables to generate and transmit more data to the mobile sink. We show that our scheme also better balance the load among nodes. Finally, we derive from the numerical results a distributed algorithm for data collection in WSN. We show through simulation that our approach leverages latency for energy saving, and we compare its performances against single-hop and multihop forwarding protocols.